Evaluation of Water Quality of Kaveri River in Tiruchirappalli District, Tamil Nadu by Principal Component Analysis

Abstract

Principal component analysis is a unique technique for reducing the dimensionality of the data. In this study, ten water quality parameters of the river Kaveri observed at five different stations of Tiruchirappalli for six years were collected and subjected to principal component analysis. A computational program was prepared in order to process and understand the data as a cluster. At first necessary data for compiling the program were listed and then fed to the program. Then the outputs were analyzed and possible linear and non-linear relationships between the water quality parameters and the timeline. It is understood that biological oxygen demand and fecal coli had a linear relationship. Further, the results suggested for group of factors that influence the water quality in a particular year.

Spatial Distribution, Sources Apportionment and Health Risk of Metals in Topsoil in Beijing, China

“…Principal component analysis (PCA) is a mathematical procedure that has been widely used in source apportionment of soil, atmosphere, and water [ 27 , 28 , 29 ]. Topsoil is mainly influenced by soil parent material and human activity during the formation process.…”